def useCSV(mass, compileOrLoad):
dummyHist = TH1F()
binMap = getBinMap()
instance("CL95cms", compileOrLoad)
compileOrLoad = "load"
massWindows = getMassWindows()
#print "massWindows dict is:"
#print massWindows
#print "massWindows[750] is: ",
#print massWindows[750]
#print "binMap dict is:"
#print binMap
response = {}
for workingPoint in binMap.keys():
#print "massWindows[mass] = massWindows[%i] is: " % mass
#print massWindows[mass]
csvInfo = fillHist_csv(dummyHist, "MC", mass, massWindows[mass], compileOrLoad)
compileOrLoad = "load"
print "for mass %i, working point %s" % (mass, workingPoint)
print csvInfo
sAndBinfo = csvInfo[workingPoint]
expectedLimitInfo = getExpectedLimit_csv(sAndBinfo["S"], sAndBinfo["B"], mass)
#print "expected limit is %f" % expectedLimitInfo["expectedLimit"]
response[workingPoint]=expectedLimitInfo["expectedLimit"]
response[compileOrLoad]=expectedLimitInfo["compileOrLoad"]
return response
def makeCosThetaPtOverMcomparisonGraphs(compileOrLoad):
HbbCutValue = 0.9
pToverMgraphs = []
cosThetagraphs = []
compileOrLoad = "compile"
massWindows = getMassWindows()
massWindows.pop(2000)
massWindows.pop(3000)
for mass in getSortedDictKeys(massWindows):
pToverMgraphs.append(TGraph())
pToverMgraphs[-1].SetNameTitle(
"M=%i_pToverM" % mass, "M=%i GeV, p_{T}/M_{j#gamma} cuts" % mass)
fillGraph_pToverM(pToverMgraphs[-1], dataOrMCbg, str(mass),
massWindows[mass], 0.9, compileOrLoad)
compileOrLoad = "load"
cosThetagraphs.append(TGraph())
cosThetagraphs[-1].SetNameTitle("M=%i_cosTheta" % mass,
"M=%i GeV, cos(#theta*) cuts" % mass)
fillGraph_cosTheta(cosThetagraphs[-1], dataOrMCbg, str(mass),
massWindows[mass], 0.9, compileOrLoad)
compileOrLoad = "load"
outfile = TFile("cosTheta_pToverM_lowMasses_HbbCut0.9.root", "RECREATE")
outfile.cd()
for graph in pToverMgraphs:
graph.Write()
for graph in cosThetagraphs:
graph.Write()
outfile.Close()
def makeOptGraphs(category, higgswindow, compileOrLoad):
#cosThetaCutValue = 0.7
print "making optgraphs for category %s, window (%i-%i)" % (
category, higgswindow[0], higgswindow[1])
graphs = []
massWindows = getMassWindows()
massWindows.pop(2000)
massWindows.pop(3000)
cutValues = getCutValues()
pToverMcutValue = cutValues["ptOverM"]
deltaRcutValue = cutValues["deltaR"]
jetEtaCutValue = cutValues["jetEta"]
phoEtaCutValue = cutValues["phEta"]
for mass in getSortedDictKeys(massWindows):
print "making S/rootB optGraph for mass %s" % mass
masswindow = massWindows[mass]
graphs.append(TGraph())
graphs[-1].SetNameTitle(
"HbbOpt", "S/#sqrt{B}, M=%s, higgs window %s-%s" %
(str(mass), str(higgswindow[0]), str(higgswindow[1])))
#print "Signal mass %f" % mass
# just keep the name from TTree::MakeClass(), don't give it a special name
samplesDirs = getSamplesDirs()
fillGraph(graphs[-1], dataOrMCbg, str(mass), higgswindow, masswindow,
category, pToverMcutValue, deltaRcutValue, jetEtaCutValue,
phoEtaCutValue, compileOrLoad)
compileOrLoad = "load"
canvas = TCanvas()
canvas.cd()
option = ""
iGraph = 0
for graph in graphs:
graph.Draw(option)
x = TColor()
graph.SetLineColor(x.GetColor(0, 0.9 - iGraph * 0.15, iGraph * 0.15))
graph.SetFillColor(kWhite)
iGraph += 1
option = "SAME"
outfile = TFile(
"HbbOpt_SoverRootB_higgsWindow_%i-%i.root" %
(higgswindow[0], higgswindow[1]), "RECREATE")
outfile.cd()
canvas.BuildLegend()
canvas.Draw()
legend = canvas.GetPrimitive("TPave")
legend.SetHeader("%s category" % category)
for prim in canvas.GetListOfPrimitives():
if "HbbOpt" in prim:
prim.SetTitle("H(b#bar{b})#gamma optimization: S/#sqrt{B}")
prim.GetXaxis().SetRangeUser(0, 2500)
canvas.Write()
outfile.Close()
bck = sigAndBGinfo["B"]
sbck = sigAndBGinfo["B"]*quadratureUncertainties
expectedLimit = CLA(ilum, slum, eff, seff, bck, sbck)
print "expected limit is: %f" % expectedLimit
compileOrLoad = "load"
response = {}
response["compileOrLoad"]="load"
response["expectedLimit"]=expectedLimit
return response
samplesDirs = getSamplesDirs()
small3sDir = samplesDirs["small3sDir"]
ddDir = samplesDirs["ddDir"]
massWindows = getMassWindows()
def useHbbTag(cosThetaCutValue):
if testTwoMasses:
del massWindows[1000]
del massWindows[2000]
graphs = []
compileOrLoad = "compile"
for mass in massWindows.keys():
graphs.append(TGraph())
graphs[-1].SetNameTitle(str(mass), str(mass))
#for i in range(-10, 20): # TODO make some reasonable way of chosing the step size and bounds for the optimization scan
# HbbCutValue = i/float(20)
for i in range(0, 4):
HbbCutValue = (i/float(3))-0.1
expectedLimitInfo = getExpectedLimit(small3sDir, ddDir, mass, massWindows[mass], HbbCutValue, cosThetaCutValue, compileOrLoad)